This data set contains simulated data that mimics customer behavior on the Starbucks rewards mobile app. Once every few days, Starbucks sends out an offer to users of the mobile app. An offer can be merely an advertisement for a drink or an actual offer such as a discount or BOGO (buy one get one free). Some users might not receive any offer during certain weeks.
Not all users receive the same offer, and that is the challenge to solve with this data set.
Your task is to combine transaction, demographic and offer data to determine which demographic groups respond best to which offer type. This data set is a simplified version of the real Starbucks app because the underlying simulator only has one product whereas Starbucks actually sells dozens of products.
Every offer has a validity period before the offer expires. As an example, a BOGO offer might be valid for only 5 days. You'll see in the data set that informational offers have a validity period even though these ads are merely providing information about a product; for example, if an informational offer has 7 days of validity, you can assume the customer is feeling the influence of the offer for 7 days after receiving the advertisement.
You'll be given transactional data showing user purchases made on the app including the timestamp of purchase and the amount of money spent on a purchase. This transactional data also has a record for each offer that a user receives as well as a record for when a user actually views the offer. There are also records for when a user completes an offer.
Keep in mind as well that someone using the app might make a purchase through the app without having received an offer or seen an offer.
To give an example, a user could receive a discount offer buy 10 dollars get 2 off on Monday. The offer is valid for 10 days from receipt. If the customer accumulates at least 10 dollars in purchases during the validity period, the customer completes the offer.
However, there are a few things to watch out for in this data set. Customers do not opt into the offers that they receive; in other words, a user can receive an offer, never actually view the offer, and still complete the offer. For example, a user might receive the "buy 10 dollars get 2 dollars off offer", but the user never opens the offer during the 10 day validity period. The customer spends 15 dollars during those ten days. There will be an offer completion record in the data set; however, the customer was not influenced by the offer because the customer never viewed the offer.
This makes data cleaning especially important and tricky.
You'll also want to take into account that some demographic groups will make purchases even if they don't receive an offer. From a business perspective, if a customer is going to make a 10 dollar purchase without an offer anyway, you wouldn't want to send a buy 10 dollars get 2 dollars off offer. You'll want to try to assess what a certain demographic group will buy when not receiving any offers.
Because this is a capstone project, you are free to analyze the data any way you see fit. For example, you could build a machine learning model that predicts how much someone will spend based on demographics and offer type. Or you could build a model that predicts whether or not someone will respond to an offer. Or, you don't need to build a machine learning model at all. You could develop a set of heuristics that determine what offer you should send to each customer (i.e., 75 percent of women customers who were 35 years old responded to offer A vs 40 percent from the same demographic to offer B, so send offer A).
The data is contained in three files:
Here is the schema and explanation of each variable in the files:
portfolio.json
profile.json
transcript.json
Note: If you are using the workspace, you will need to go to the terminal and run the command conda update pandas before reading in the files. This is because the version of pandas in the workspace cannot read in the transcript.json file correctly, but the newest version of pandas can. You can access the termnal from the orange icon in the top left of this notebook.
You can see how to access the terminal and how the install works using the two images below. First you need to access the terminal:

Then you will want to run the above command:

Finally, when you enter back into the notebook (use the jupyter icon again), you should be able to run the below cell without any errors.
# import libraries here; add more as necessary
import numpy as np
import pandas as pd
import math
import json
import pickle
from datetime import datetime as dt
from IPython.display import display, HTML
import plotly
import matplotlib.pyplot as plt
import seaborn as sns
import re
# magic word for producing visualizations in notebook
%matplotlib inline
from sklearn import preprocessing as p
from sklearn.decomposition import PCA
from sklearn.cluster import KMeans
from sklearn.metrics import classification_report
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import confusion_matrix
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline, FeatureUnion
from sklearn.ensemble import AdaBoostClassifier
from sklearn import svm
import sys
np.set_printoptions(threshold=sys.maxsize)
print(sys.version)
# Set figure width to 12 and height to 9
fig_size = plt.rcParams["figure.figsize"]
fig_size[0] = 15
fig_size[1] = 10
plt.rcParams["figure.figsize"] = fig_size
pd.set_option('display.max_columns', 500)
import chart_studio as py
import plotly.graph_objects as go
import plotly.io as pio
import plotly.express as px
from plotly.subplots import make_subplots
3.7.3 (default, Mar 27 2019, 22:11:17) [GCC 7.3.0]
# read in the json files
portfolio = pd.read_json('data/portfolio.json', orient='records', lines=True)
profile = pd.read_json('data/profile.json', orient='records', lines=True)
transcript = pd.read_json('data/transcript.json', orient='records', lines=True)
portfolio
| channels | difficulty | duration | id | offer_type | reward | |
|---|---|---|---|---|---|---|
| 0 | [email, mobile, social] | 10 | 7 | ae264e3637204a6fb9bb56bc8210ddfd | bogo | 10 |
| 1 | [web, email, mobile, social] | 10 | 5 | 4d5c57ea9a6940dd891ad53e9dbe8da0 | bogo | 10 |
| 2 | [web, email, mobile] | 0 | 4 | 3f207df678b143eea3cee63160fa8bed | informational | 0 |
| 3 | [web, email, mobile] | 5 | 7 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | bogo | 5 |
| 4 | [web, email] | 20 | 10 | 0b1e1539f2cc45b7b9fa7c272da2e1d7 | discount | 5 |
| 5 | [web, email, mobile, social] | 7 | 7 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | discount | 3 |
| 6 | [web, email, mobile, social] | 10 | 10 | fafdcd668e3743c1bb461111dcafc2a4 | discount | 2 |
| 7 | [email, mobile, social] | 0 | 3 | 5a8bc65990b245e5a138643cd4eb9837 | informational | 0 |
| 8 | [web, email, mobile, social] | 5 | 5 | f19421c1d4aa40978ebb69ca19b0e20d | bogo | 5 |
| 9 | [web, email, mobile] | 10 | 7 | 2906b810c7d4411798c6938adc9daaa5 | discount | 2 |
profile
| age | became_member_on | gender | id | income | |
|---|---|---|---|---|---|
| 0 | 118 | 20170212 | None | 68be06ca386d4c31939f3a4f0e3dd783 | NaN |
| 1 | 55 | 20170715 | F | 0610b486422d4921ae7d2bf64640c50b | 112000.0 |
| 2 | 118 | 20180712 | None | 38fe809add3b4fcf9315a9694bb96ff5 | NaN |
| 3 | 75 | 20170509 | F | 78afa995795e4d85b5d9ceeca43f5fef | 100000.0 |
| 4 | 118 | 20170804 | None | a03223e636434f42ac4c3df47e8bac43 | NaN |
| 5 | 68 | 20180426 | M | e2127556f4f64592b11af22de27a7932 | 70000.0 |
| 6 | 118 | 20170925 | None | 8ec6ce2a7e7949b1bf142def7d0e0586 | NaN |
| 7 | 118 | 20171002 | None | 68617ca6246f4fbc85e91a2a49552598 | NaN |
| 8 | 65 | 20180209 | M | 389bc3fa690240e798340f5a15918d5c | 53000.0 |
| 9 | 118 | 20161122 | None | 8974fc5686fe429db53ddde067b88302 | NaN |
| 10 | 118 | 20170824 | None | c4863c7985cf408faee930f111475da3 | NaN |
| 11 | 118 | 20150919 | None | 148adfcaa27d485b82f323aaaad036bd | NaN |
| 12 | 58 | 20171111 | M | 2eeac8d8feae4a8cad5a6af0499a211d | 51000.0 |
| 13 | 61 | 20170911 | F | aa4862eba776480b8bb9c68455b8c2e1 | 57000.0 |
| 14 | 26 | 20140213 | M | e12aeaf2d47d42479ea1c4ac3d8286c6 | 46000.0 |
| 15 | 62 | 20160211 | F | 31dda685af34476cad5bc968bdb01c53 | 71000.0 |
| 16 | 49 | 20141113 | M | 62cf5e10845442329191fc246e7bcea3 | 52000.0 |
| 17 | 118 | 20170801 | None | 744d603ef08c4f33af5a61c8c7628d1c | NaN |
| 18 | 57 | 20171231 | M | 6445de3b47274c759400cd68131d91b4 | 42000.0 |
| 19 | 61 | 20180501 | F | a448667f336b42c9a66fc5ffd5d73772 | 40000.0 |
| 20 | 40 | 20160504 | F | 440cf1fd7580490c971d8c651ed962af | 71000.0 |
| 21 | 64 | 20170909 | M | 4b0da7e80e5945209a1fdddfe813dbe0 | 100000.0 |
| 22 | 78 | 20170616 | F | c27e0d6ab72c455a8bb66d980963de60 | 71000.0 |
| 23 | 118 | 20170907 | None | 2b826eba31074a059d63b0ae8f50b7d5 | NaN |
| 24 | 42 | 20130811 | M | f806632c011441378d4646567f357a21 | 69000.0 |
| 25 | 56 | 20180428 | F | d058f73bf8674a26a95227db098147b1 | 88000.0 |
| 26 | 118 | 20170330 | None | 65aba5c617294649aeb624da249e1ee5 | NaN |
| 27 | 33 | 20170926 | F | c6c9884912c645429f3333f912b55f44 | 52000.0 |
| 28 | 46 | 20170911 | F | 7429a044884842d6862f516c38b1156f | 59000.0 |
| 29 | 59 | 20150121 | M | ebe7ef46ea6f4963a7dd49f501b26779 | 41000.0 |
| ... | ... | ... | ... | ... | ... |
| 16970 | 67 | 20151107 | M | a2e6029e17b6466187a40b66e333a73e | 94000.0 |
| 16971 | 52 | 20180522 | F | 6e71b66784844d1ab8376ac8ab096d4b | 75000.0 |
| 16972 | 44 | 20170119 | F | e2fd53ed790240c586b3188f23542cca | 51000.0 |
| 16973 | 30 | 20151012 | M | 08eb126ad33f447ca3ad076482445c05 | 57000.0 |
| 16974 | 59 | 20160113 | F | f88e91a11d8f405b9a47ad3741415b83 | 71000.0 |
| 16975 | 61 | 20171231 | F | 1b4df4b48bf64727a4c445909aea1251 | 81000.0 |
| 16976 | 39 | 20160921 | F | 122c0c2a3c2540848f8c3fdc37e97639 | 54000.0 |
| 16977 | 118 | 20160609 | None | eb7dd979f4644052a5c401a01f129132 | NaN |
| 16978 | 29 | 20170220 | F | 54bead4179c44b71acc4e8398181d183 | 58000.0 |
| 16979 | 63 | 20130922 | F | a00058cf10334a308c68e7631c529907 | 52000.0 |
| 16980 | 118 | 20160901 | None | 5c686d09ca4d475a8f750f2ba07e0440 | NaN |
| 16981 | 84 | 20160629 | M | 1966fa40d2f84620b2b1b9b64f8e0209 | 93000.0 |
| 16982 | 118 | 20160415 | None | d9ca82f550ac4ee58b6299cf1e5c824a | NaN |
| 16983 | 72 | 20150404 | F | ff737c250d2343729ade04c4f6eb1001 | 65000.0 |
| 16984 | 75 | 20160716 | F | 392d23b2c958493197f647bedfe4f418 | 78000.0 |
| 16985 | 26 | 20180619 | M | 97ee6e7a12fe4064b260fa48bdd0330f | 55000.0 |
| 16986 | 59 | 20170731 | F | bf3069b178fe40d789dd027901bc406b | 63000.0 |
| 16987 | 57 | 20160709 | M | 76ddbd6576844afe811f1a3c0fbb5bec | 40000.0 |
| 16988 | 64 | 20180104 | M | f653cf2d8bba42d0a53c2937ee2e5893 | 51000.0 |
| 16989 | 118 | 20180305 | None | ca45ee1883624304bac1e4c8a114f045 | NaN |
| 16990 | 70 | 20160310 | F | 79edb810789c447e8d212a324b44cc16 | 39000.0 |
| 16991 | 118 | 20160116 | None | a9a20fa8b5504360beb4e7c8712f8306 | NaN |
| 16992 | 21 | 20170917 | F | 400d0536e8794cbb855b0d882d67cbda | 72000.0 |
| 16993 | 60 | 20180505 | M | cb23b66c56f64b109d673d5e56574529 | 113000.0 |
| 16994 | 118 | 20151211 | None | c02b10e8752c4d8e9b73f918558531f7 | NaN |
| 16995 | 45 | 20180604 | F | 6d5f3a774f3d4714ab0c092238f3a1d7 | 54000.0 |
| 16996 | 61 | 20180713 | M | 2cb4f97358b841b9a9773a7aa05a9d77 | 72000.0 |
| 16997 | 49 | 20170126 | M | 01d26f638c274aa0b965d24cefe3183f | 73000.0 |
| 16998 | 83 | 20160307 | F | 9dc1421481194dcd9400aec7c9ae6366 | 50000.0 |
| 16999 | 62 | 20170722 | F | e4052622e5ba45a8b96b59aba68cf068 | 82000.0 |
17000 rows × 5 columns
transcript
| event | person | time | value | |
|---|---|---|---|---|
| 0 | offer received | 78afa995795e4d85b5d9ceeca43f5fef | 0 | {'offer id': '9b98b8c7a33c4b65b9aebfe6a799e6d9'} |
| 1 | offer received | a03223e636434f42ac4c3df47e8bac43 | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 2 | offer received | e2127556f4f64592b11af22de27a7932 | 0 | {'offer id': '2906b810c7d4411798c6938adc9daaa5'} |
| 3 | offer received | 8ec6ce2a7e7949b1bf142def7d0e0586 | 0 | {'offer id': 'fafdcd668e3743c1bb461111dcafc2a4'} |
| 4 | offer received | 68617ca6246f4fbc85e91a2a49552598 | 0 | {'offer id': '4d5c57ea9a6940dd891ad53e9dbe8da0'} |
| 5 | offer received | 389bc3fa690240e798340f5a15918d5c | 0 | {'offer id': 'f19421c1d4aa40978ebb69ca19b0e20d'} |
| 6 | offer received | c4863c7985cf408faee930f111475da3 | 0 | {'offer id': '2298d6c36e964ae4a3e7e9706d1fb8c2'} |
| 7 | offer received | 2eeac8d8feae4a8cad5a6af0499a211d | 0 | {'offer id': '3f207df678b143eea3cee63160fa8bed'} |
| 8 | offer received | aa4862eba776480b8bb9c68455b8c2e1 | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 9 | offer received | 31dda685af34476cad5bc968bdb01c53 | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 10 | offer received | 744d603ef08c4f33af5a61c8c7628d1c | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 11 | offer received | 3d02345581554e81b7b289ab5e288078 | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 12 | offer received | 4b0da7e80e5945209a1fdddfe813dbe0 | 0 | {'offer id': 'ae264e3637204a6fb9bb56bc8210ddfd'} |
| 13 | offer received | c27e0d6ab72c455a8bb66d980963de60 | 0 | {'offer id': '3f207df678b143eea3cee63160fa8bed'} |
| 14 | offer received | d53717f5400c4e84affdaeda9dd926b3 | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 15 | offer received | f806632c011441378d4646567f357a21 | 0 | {'offer id': 'fafdcd668e3743c1bb461111dcafc2a4'} |
| 16 | offer received | d058f73bf8674a26a95227db098147b1 | 0 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 17 | offer received | 65aba5c617294649aeb624da249e1ee5 | 0 | {'offer id': '2906b810c7d4411798c6938adc9daaa5'} |
| 18 | offer received | ebe7ef46ea6f4963a7dd49f501b26779 | 0 | {'offer id': '9b98b8c7a33c4b65b9aebfe6a799e6d9'} |
| 19 | offer received | 1e9420836d554513ab90eba98552d0a9 | 0 | {'offer id': 'ae264e3637204a6fb9bb56bc8210ddfd'} |
| 20 | offer received | 868317b9be554cb18e50bc68484749a2 | 0 | {'offer id': '2906b810c7d4411798c6938adc9daaa5'} |
| 21 | offer received | f082d80f0aac47a99173ba8ef8fc1909 | 0 | {'offer id': '9b98b8c7a33c4b65b9aebfe6a799e6d9'} |
| 22 | offer received | 102e9454054946fda62242d2e176fdce | 0 | {'offer id': '4d5c57ea9a6940dd891ad53e9dbe8da0'} |
| 23 | offer received | 4beeb3ed64dd4898b0edf2f6b67426d3 | 0 | {'offer id': '2906b810c7d4411798c6938adc9daaa5'} |
| 24 | offer received | 9f30b375d7bd4c62a884ffe7034e09ee | 0 | {'offer id': '2298d6c36e964ae4a3e7e9706d1fb8c2'} |
| 25 | offer received | 25c906289d154b66bf579693f89481c9 | 0 | {'offer id': '2906b810c7d4411798c6938adc9daaa5'} |
| 26 | offer received | 6e014185620b49bd98749f728747572f | 0 | {'offer id': 'f19421c1d4aa40978ebb69ca19b0e20d'} |
| 27 | offer received | 02c083884c7d45b39cc68e1314fec56c | 0 | {'offer id': 'ae264e3637204a6fb9bb56bc8210ddfd'} |
| 28 | offer received | c0d210398dee4a0895b24444a5fcd1d2 | 0 | {'offer id': '9b98b8c7a33c4b65b9aebfe6a799e6d9'} |
| 29 | offer received | 8be4463721e14d7fa600686bf8c8b2ed | 0 | {'offer id': 'fafdcd668e3743c1bb461111dcafc2a4'} |
| ... | ... | ... | ... | ... |
| 306504 | transaction | 8524d450673b4c24869b6c94380006de | 714 | {'amount': 4.89} |
| 306505 | transaction | b895c57e8cd047a8872ce02aa54759d6 | 714 | {'amount': 4.48} |
| 306506 | offer completed | b895c57e8cd047a8872ce02aa54759d6 | 714 | {'offer_id': 'fafdcd668e3743c1bb461111dcafc2a4... |
| 306507 | offer viewed | 8dda575c2a1d44b9ac8e8b07b93d1f8e | 714 | {'offer id': '0b1e1539f2cc45b7b9fa7c272da2e1d7'} |
| 306508 | transaction | 8431c16f8e1d440880db371a68f82dd0 | 714 | {'amount': 1.19} |
| 306509 | offer completed | 8431c16f8e1d440880db371a68f82dd0 | 714 | {'offer_id': 'fafdcd668e3743c1bb461111dcafc2a4... |
| 306510 | transaction | ba620885e51c4b0ea64a4f61daad494f | 714 | {'amount': 14.31} |
| 306511 | transaction | a1a8f40407c444cc848468275308958a | 714 | {'amount': 2.37} |
| 306512 | transaction | 8d80970192fa496f99d6b45c470a4b60 | 714 | {'amount': 6.92} |
| 306513 | transaction | bde275066f3c4fa0bff3093e3b866a2c | 714 | {'amount': 12.73} |
| 306514 | transaction | f1e4fd36e5a0446f83861308bddf6945 | 714 | {'amount': 8.2} |
| 306515 | transaction | 0b64be3b241c4407a5c9a71781173829 | 714 | {'amount': 2.6} |
| 306516 | transaction | 86d03d35d7e0434b935e7743e83be3a0 | 714 | {'amount': 9.2} |
| 306517 | transaction | 3408fd05c781401f8442fb6dbaaea9c7 | 714 | {'amount': 11.7} |
| 306518 | transaction | 1593d617fac246ef8e50dbb0ffd77f5f | 714 | {'amount': 40.67} |
| 306519 | transaction | f1b31d07b5d84f69a2d5f1d07843989e | 714 | {'amount': 31.13} |
| 306520 | transaction | 2ce987015ec0404a97ba333e8e814090 | 714 | {'amount': 1.6400000000000001} |
| 306521 | transaction | 2e33545f0a764d27b2ccff95fc8d72c4 | 714 | {'amount': 17.35} |
| 306522 | transaction | d1c4500ace2e45e9a45d3cd2fccac8d8 | 714 | {'amount': 4.42} |
| 306523 | transaction | b65affd9e07346a1906364a396950e3d | 714 | {'amount': 18.35} |
| 306524 | transaction | d613ca9c59dd42f497bdbf6178da54a7 | 714 | {'amount': 25.14} |
| 306525 | transaction | eec70ab28af74a22a4aeb889c0317944 | 714 | {'amount': 43.58} |
| 306526 | transaction | 24f56b5e1849462093931b164eb803b5 | 714 | {'amount': 22.64} |
| 306527 | offer completed | 24f56b5e1849462093931b164eb803b5 | 714 | {'offer_id': 'fafdcd668e3743c1bb461111dcafc2a4... |
| 306528 | transaction | 5ca2620962114246ab218fc648eb3934 | 714 | {'amount': 2.2} |
| 306529 | transaction | b3a1272bc9904337b331bf348c3e8c17 | 714 | {'amount': 1.5899999999999999} |
| 306530 | transaction | 68213b08d99a4ae1b0dcb72aebd9aa35 | 714 | {'amount': 9.53} |
| 306531 | transaction | a00058cf10334a308c68e7631c529907 | 714 | {'amount': 3.61} |
| 306532 | transaction | 76ddbd6576844afe811f1a3c0fbb5bec | 714 | {'amount': 3.5300000000000002} |
| 306533 | transaction | c02b10e8752c4d8e9b73f918558531f7 | 714 | {'amount': 4.05} |
306534 rows × 4 columns
# since any offer just started does not have any effect on the user therefore on our analysis and its outcome,
# we will take any transcript item with time = 0 from the transcript dataframe.
transcript.shape[0] - transcript[transcript['time']!=0].shape[0]
15561
profile.describe()
| age | became_member_on | income | |
|---|---|---|---|
| count | 17000.000000 | 1.700000e+04 | 14825.000000 |
| mean | 62.531412 | 2.016703e+07 | 65404.991568 |
| std | 26.738580 | 1.167750e+04 | 21598.299410 |
| min | 18.000000 | 2.013073e+07 | 30000.000000 |
| 25% | 45.000000 | 2.016053e+07 | 49000.000000 |
| 50% | 58.000000 | 2.017080e+07 | 64000.000000 |
| 75% | 73.000000 | 2.017123e+07 | 80000.000000 |
| max | 118.000000 | 2.018073e+07 | 120000.000000 |
transcript.describe()
| time | |
|---|---|
| count | 306534.000000 |
| mean | 366.382940 |
| std | 200.326314 |
| min | 0.000000 |
| 25% | 186.000000 |
| 50% | 408.000000 |
| 75% | 528.000000 |
| max | 714.000000 |
def get_days(item_time_in_hours):
item_days = int(round(item_time_in_hours / 24))
return item_days
def extract_key_value(item_value):
value_key = list(item_value)[0]
item_amount = ''
item_offer_id = ''
if value_key == 'amount':
item_amount = item_value[value_key]
if value_key == 'offer id':
item_offer_id = item_value[value_key]
if value_key == 'offer_id':
item_offer_id = item_value[value_key]
return pd.Series([item_amount, item_offer_id])
def extract_event(item_event):
offer_received = 0
offer_viewed = 0
offer_completed = 0
transaction = 0
if item_event == 'offer received':
offer_received = 1
if item_event == 'offer viewed':
offer_viewed = 1
if item_event == 'offer completed':
offer_completed = 1
if item_event == 'transaction':
transaction = 1
return pd.Series([offer_received, offer_viewed, offer_completed, transaction])
def clean_transcript(transcript_df):
transcript_cleaned_df = transcript_df.copy()
transcript_cleaned_df = transcript_cleaned_df[transcript_cleaned_df['time']!=0]
transcript_cleaned_df[['transaction_amount','offer_id']] = transcript_cleaned_df.apply(lambda x: extract_key_value(x['value']), axis=1)
transcript_cleaned_df[['offer_status_received', 'offer_status_viewed','offer_status_completed', 'transaction']] = transcript_cleaned_df.apply(lambda x: extract_event(x['event']), axis=1)
transcript_cleaned_df['offer_days'] = transcript_cleaned_df.apply(lambda x: get_days(x['time']), axis=1)
transcript_cleaned_df['user_id'] = transcript_cleaned_df['person']
transcript_cleaned_df.drop(['event','time','value','person'], axis=1, inplace=True)
transcript_cleaned_df = transcript_cleaned_df[['user_id','offer_id','transaction_amount','offer_days', 'offer_status_received','offer_status_viewed','offer_status_completed']]
return transcript_cleaned_df
transcript_df = clean_transcript(transcript)
transcript_df
| user_id | offer_id | transaction_amount | offer_days | offer_status_received | offer_status_viewed | offer_status_completed | |
|---|---|---|---|---|---|---|---|
| 15561 | 78afa995795e4d85b5d9ceeca43f5fef | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | |
| 15562 | a03223e636434f42ac4c3df47e8bac43 | 0b1e1539f2cc45b7b9fa7c272da2e1d7 | 0 | 0 | 1 | 0 | |
| 15563 | 102e9454054946fda62242d2e176fdce | 19.88 | 0 | 0 | 0 | 0 | |
| 15564 | 102e9454054946fda62242d2e176fdce | 4d5c57ea9a6940dd891ad53e9dbe8da0 | 0 | 0 | 0 | 1 | |
| 15565 | 02c083884c7d45b39cc68e1314fec56c | 1.44 | 0 | 0 | 0 | 0 | |
| 15566 | be8a5d1981a2458d90b255ddc7e0d174 | 2.63 | 0 | 0 | 0 | 0 | |
| 15567 | 7584948ea6d04f94b8798624706261c2 | 4d5c57ea9a6940dd891ad53e9dbe8da0 | 0 | 0 | 1 | 0 | |
| 15568 | a5a6ef2b78a04ddc9f374dd7c7f60bff | 5a8bc65990b245e5a138643cd4eb9837 | 0 | 0 | 1 | 0 | |
| 15569 | 8045834137dc47faa24f2c4547969f33 | f19421c1d4aa40978ebb69ca19b0e20d | 0 | 0 | 1 | 0 | |
| 15570 | 571b739ada3041fb8fbd20f23ce034f7 | 4d5c57ea9a6940dd891ad53e9dbe8da0 | 0 | 0 | 1 | 0 | |
| 15571 | a9780228a1d04539afdee8b745e4be10 | fafdcd668e3743c1bb461111dcafc2a4 | 0 | 0 | 1 | 0 | |
| 15572 | 13033baa9d294c3c9165a00d71b72614 | 2906b810c7d4411798c6938adc9daaa5 | 0 | 0 | 1 | 0 | |
| 15573 | 2cf5895bddf9467e878c6d51a622d5fb | f19421c1d4aa40978ebb69ca19b0e20d | 0 | 0 | 1 | 0 | |
| 15574 | 6747dda08bed46298c23e05b64820a3a | 7.32 | 0 | 0 | 0 | 0 | |
| 15575 | f35b342b24734da18a830bb9329a4fbd | 4d5c57ea9a6940dd891ad53e9dbe8da0 | 0 | 0 | 1 | 0 | |
| 15576 | 37a97f6e09784a07bbb67bc6539f1a00 | 3f207df678b143eea3cee63160fa8bed | 0 | 0 | 1 | 0 | |
| 15577 | 37a97f6e09784a07bbb67bc6539f1a00 | 24.25 | 0 | 0 | 0 | 0 | |
| 15578 | fe97aa22dd3e48c8b143116a8403dd52 | fafdcd668e3743c1bb461111dcafc2a4 | 0 | 0 | 1 | 0 | |
| 15579 | d7dc31e069124ef49e1bb937cb89f41c | 4d5c57ea9a6940dd891ad53e9dbe8da0 | 0 | 0 | 1 | 0 | |
| 15580 | d250372c924747d8ac9a8fa88f584bc3 | f19421c1d4aa40978ebb69ca19b0e20d | 0 | 0 | 1 | 0 | |
| 15581 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | |
| 15582 | ae47fbe72b274838a2093c3e91bc03dc | ae264e3637204a6fb9bb56bc8210ddfd | 0 | 0 | 1 | 0 | |
| 15583 | e737ff591120415581ddbe817b8c82ca | 23.27 | 0 | 0 | 0 | 0 | |
| 15584 | 32189735a963491082e35dd4c3221690 | 21.22 | 0 | 0 | 0 | 0 | |
| 15585 | 18174519037241e9b1ddcb627ca4dc41 | 5a8bc65990b245e5a138643cd4eb9837 | 0 | 0 | 1 | 0 | |
| 15586 | 031387fa9cfd47e88f4e4b4b4cb71925 | fafdcd668e3743c1bb461111dcafc2a4 | 0 | 0 | 1 | 0 | |
| 15587 | 09e7e40eb89943458f4f79fe2e023dd6 | fafdcd668e3743c1bb461111dcafc2a4 | 0 | 0 | 1 | 0 | |
| 15588 | c894971c9e414a358b84255199727636 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 0 | 0 | 1 | 0 | |
| 15589 | c894971c9e414a358b84255199727636 | 6.97 | 0 | 0 | 0 | 0 | |
| 15590 | 00c6035df45840038a72766c6d27a0db | fafdcd668e3743c1bb461111dcafc2a4 | 0 | 0 | 1 | 0 | |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 306504 | 8524d450673b4c24869b6c94380006de | 4.89 | 30 | 0 | 0 | 0 | |
| 306505 | b895c57e8cd047a8872ce02aa54759d6 | 4.48 | 30 | 0 | 0 | 0 | |
| 306506 | b895c57e8cd047a8872ce02aa54759d6 | fafdcd668e3743c1bb461111dcafc2a4 | 30 | 0 | 0 | 1 | |
| 306507 | 8dda575c2a1d44b9ac8e8b07b93d1f8e | 0b1e1539f2cc45b7b9fa7c272da2e1d7 | 30 | 0 | 1 | 0 | |
| 306508 | 8431c16f8e1d440880db371a68f82dd0 | 1.19 | 30 | 0 | 0 | 0 | |
| 306509 | 8431c16f8e1d440880db371a68f82dd0 | fafdcd668e3743c1bb461111dcafc2a4 | 30 | 0 | 0 | 1 | |
| 306510 | ba620885e51c4b0ea64a4f61daad494f | 14.31 | 30 | 0 | 0 | 0 | |
| 306511 | a1a8f40407c444cc848468275308958a | 2.37 | 30 | 0 | 0 | 0 | |
| 306512 | 8d80970192fa496f99d6b45c470a4b60 | 6.92 | 30 | 0 | 0 | 0 | |
| 306513 | bde275066f3c4fa0bff3093e3b866a2c | 12.73 | 30 | 0 | 0 | 0 | |
| 306514 | f1e4fd36e5a0446f83861308bddf6945 | 8.2 | 30 | 0 | 0 | 0 | |
| 306515 | 0b64be3b241c4407a5c9a71781173829 | 2.6 | 30 | 0 | 0 | 0 | |
| 306516 | 86d03d35d7e0434b935e7743e83be3a0 | 9.2 | 30 | 0 | 0 | 0 | |
| 306517 | 3408fd05c781401f8442fb6dbaaea9c7 | 11.7 | 30 | 0 | 0 | 0 | |
| 306518 | 1593d617fac246ef8e50dbb0ffd77f5f | 40.67 | 30 | 0 | 0 | 0 | |
| 306519 | f1b31d07b5d84f69a2d5f1d07843989e | 31.13 | 30 | 0 | 0 | 0 | |
| 306520 | 2ce987015ec0404a97ba333e8e814090 | 1.64 | 30 | 0 | 0 | 0 | |
| 306521 | 2e33545f0a764d27b2ccff95fc8d72c4 | 17.35 | 30 | 0 | 0 | 0 | |
| 306522 | d1c4500ace2e45e9a45d3cd2fccac8d8 | 4.42 | 30 | 0 | 0 | 0 | |
| 306523 | b65affd9e07346a1906364a396950e3d | 18.35 | 30 | 0 | 0 | 0 | |
| 306524 | d613ca9c59dd42f497bdbf6178da54a7 | 25.14 | 30 | 0 | 0 | 0 | |
| 306525 | eec70ab28af74a22a4aeb889c0317944 | 43.58 | 30 | 0 | 0 | 0 | |
| 306526 | 24f56b5e1849462093931b164eb803b5 | 22.64 | 30 | 0 | 0 | 0 | |
| 306527 | 24f56b5e1849462093931b164eb803b5 | fafdcd668e3743c1bb461111dcafc2a4 | 30 | 0 | 0 | 1 | |
| 306528 | 5ca2620962114246ab218fc648eb3934 | 2.2 | 30 | 0 | 0 | 0 | |
| 306529 | b3a1272bc9904337b331bf348c3e8c17 | 1.59 | 30 | 0 | 0 | 0 | |
| 306530 | 68213b08d99a4ae1b0dcb72aebd9aa35 | 9.53 | 30 | 0 | 0 | 0 | |
| 306531 | a00058cf10334a308c68e7631c529907 | 3.61 | 30 | 0 | 0 | 0 | |
| 306532 | 76ddbd6576844afe811f1a3c0fbb5bec | 3.53 | 30 | 0 | 0 | 0 | |
| 306533 | c02b10e8752c4d8e9b73f918558531f7 | 4.05 | 30 | 0 | 0 | 0 |
290973 rows × 7 columns
portfolio
| channels | difficulty | duration | id | offer_type | reward | |
|---|---|---|---|---|---|---|
| 0 | [email, mobile, social] | 10 | 7 | ae264e3637204a6fb9bb56bc8210ddfd | bogo | 10 |
| 1 | [web, email, mobile, social] | 10 | 5 | 4d5c57ea9a6940dd891ad53e9dbe8da0 | bogo | 10 |
| 2 | [web, email, mobile] | 0 | 4 | 3f207df678b143eea3cee63160fa8bed | informational | 0 |
| 3 | [web, email, mobile] | 5 | 7 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | bogo | 5 |
| 4 | [web, email] | 20 | 10 | 0b1e1539f2cc45b7b9fa7c272da2e1d7 | discount | 5 |
| 5 | [web, email, mobile, social] | 7 | 7 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | discount | 3 |
| 6 | [web, email, mobile, social] | 10 | 10 | fafdcd668e3743c1bb461111dcafc2a4 | discount | 2 |
| 7 | [email, mobile, social] | 0 | 3 | 5a8bc65990b245e5a138643cd4eb9837 | informational | 0 |
| 8 | [web, email, mobile, social] | 5 | 5 | f19421c1d4aa40978ebb69ca19b0e20d | bogo | 5 |
| 9 | [web, email, mobile] | 10 | 7 | 2906b810c7d4411798c6938adc9daaa5 | discount | 2 |
def get_channels(item_channels):
web = 0
email = 0
mobile = 0
social = 0
for i in item_channels:
if i == 'web':
web = 1
if i == 'email':
email = 1
if i == 'mobile':
mobile = 1
if i == 'social':
social = 1
return pd.Series([web, email, mobile, social])
def get_offer_type(offer_type):
bogo = 0
discount = 0
informational = 0
if offer_type == 'bogo':
bogo = 1
if offer_type == 'discount':
discount = 1
if offer_type == 'informational':
informational = 1
return pd.Series([bogo, discount, informational])
def clean_portfolio(portfolio_df):
portfolio_df_clean = portfolio_df.copy()
offer_ids_list = list(pd.get_dummies(portfolio_df_clean['id'], prefix='offer_id_'))
offer_ids_dummies = pd.get_dummies(portfolio_df_clean['id'], prefix='offer_id_')
portfolio_df_clean[offer_ids_list] = offer_ids_dummies
portfolio_df_clean[['web', 'email', 'mobile', 'social']] = portfolio_df_clean.apply(lambda x: get_channels(x['channels']), axis=1)
portfolio_df_clean[['bogo', 'discount', 'informational']] = portfolio_df_clean.apply(lambda x: get_offer_type(x['offer_type']), axis=1)
portfolio_df_clean.drop(['channels'], axis=1, inplace=True)
portfolio_df_clean.drop(['offer_type'], axis=1, inplace=True)
portfolio_df_clean['offer_id'] = portfolio_df_clean['id']
portfolio_df_clean['offer_duration'] = portfolio_df_clean['duration']
portfolio_df_clean['offer_difficulty'] = portfolio_df_clean['difficulty']
portfolio_df_clean['offer_reward'] = portfolio_df_clean['reward']
portfolio_df_clean['offer_type_bogo'] = portfolio_df_clean['bogo']
portfolio_df_clean['offer_type_discount'] = portfolio_df_clean['discount']
portfolio_df_clean['offer_type_informational'] = portfolio_df_clean['informational']
portfolio_df_clean['offer_channel_web'] = portfolio_df_clean['web']
portfolio_df_clean['offer_channel_email'] = portfolio_df_clean['email']
portfolio_df_clean['offer_channel_mobile'] = portfolio_df_clean['mobile']
portfolio_df_clean['offer_channel_social'] = portfolio_df_clean['social']
portfolio_df_clean = portfolio_df_clean[['offer_id','offer_duration','offer_difficulty','offer_reward','offer_type_bogo','offer_type_discount','offer_type_informational','offer_channel_web','offer_channel_email','offer_channel_mobile','offer_channel_social'] + offer_ids_list]
return portfolio_df_clean
portfolio_df = clean_portfolio(portfolio)
portfolio_df
| offer_id | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | ae264e3637204a6fb9bb56bc8210ddfd | 7 | 10 | 10 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 1 | 4d5c57ea9a6940dd891ad53e9dbe8da0 | 5 | 10 | 10 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 2 | 3f207df678b143eea3cee63160fa8bed | 4 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 7 | 5 | 5 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 4 | 0b1e1539f2cc45b7b9fa7c272da2e1d7 | 10 | 20 | 5 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 5 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 7 | 7 | 3 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 6 | fafdcd668e3743c1bb461111dcafc2a4 | 10 | 10 | 2 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 7 | 5a8bc65990b245e5a138643cd4eb9837 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 8 | f19421c1d4aa40978ebb69ca19b0e20d | 5 | 5 | 5 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| 9 | 2906b810c7d4411798c6938adc9daaa5 | 7 | 10 | 2 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
profile['age'].describe()
count 17000.000000 mean 62.531412 std 26.738580 min 18.000000 25% 45.000000 50% 58.000000 75% 73.000000 max 118.000000 Name: age, dtype: float64
profile['age'].hist()
<matplotlib.axes._subplots.AxesSubplot at 0x7fc91ba97780>
profile['income'].hist()
<matplotlib.axes._subplots.AxesSubplot at 0x7fc91ba5aa58>
gender_group = ['user_gender_F', 'user_gender_M', 'user_gender_O']
gender_group_info = ['Male','Female', 'Other']
age_group = ['user_age_group_1', 'user_age_group_2', 'user_age_group_3', 'user_age_group_4', 'user_age_group_5', 'user_age_group_6', 'user_age_group_7']
age_group_info = ['21 or younger','25 - 22', '35 - 26', '45 - 36', '55 - 46', '65 - 56', '66 or older']
loyality_group = ['user_loyality_group_1', 'user_loyality_group_2', 'user_loyality_group_3', 'user_loyality_group_4', 'user_loyality_group_5', 'user_loyality_group_6', 'user_loyality_group_7']
loyality_group_info = ['2013 or newer','2014 - 2013', '2015 - 2014', '2016 - 2015', '2017 - 2016', '2018 - 2017', '2018 or newer']
income_group = ['user_income_group_1', 'user_income_group_2', 'user_income_group_3', 'user_income_group_4', 'user_income_group_5', 'user_income_group_6', 'user_income_group_7']
income_group_info = ['35k or less','45k - 36k', '65k - 46k', '75k - 66k', '85k - 76k', '95k - 86k', '96k or more']
def age_group(age):
if age <= 21:
return 1
if age <= 25:
return 2
if age <= 35:
return 3
if age <= 45:
return 4
if age <= 55:
return 5
if age <= 65:
return 6
if age > 65:
return 7
def income_group(income):
if income <= 35000:
return 1
if income <= 45000:
return 2
if income <= 65000:
return 3
if income <= 75000:
return 4
if income <= 85000:
return 5
if income <= 95000:
return 6
if income > 95000:
return 7
def loyality_group(loyality):
if loyality <= 20130000:
return 1
if loyality <= 20140000:
return 2
if loyality <= 20150000:
return 3
if loyality <= 20160000:
return 4
if loyality <= 20170000:
return 5
if loyality <= 20180000:
return 6
if loyality > 20180000:
return 7
def clean_profile(profile_df):
profile_df_cleaned = profile_df.copy()
profile_df_cleaned = profile_df_cleaned.dropna()
profile_df_cleaned[['user_gender_F','user_gender_M','user_gender_O']] = pd.get_dummies(profile_df_cleaned['gender'])
profile_df_cleaned['user_id'] = profile_df_cleaned['id']
profile_df_cleaned['user_age_group'] = profile_df_cleaned['age'].apply(lambda x: age_group(x))
profile_df_cleaned = pd.concat([profile_df_cleaned.drop('user_age_group', axis=1),pd.get_dummies(profile_df_cleaned['user_age_group'],prefix='user_age_group')], axis=1)
profile_df_cleaned['user_loyality_group'] = profile_df_cleaned['became_member_on'].apply(lambda x: loyality_group(x))
profile_df_cleaned = pd.concat([profile_df_cleaned.drop('user_loyality_group', axis=1),pd.get_dummies(profile_df_cleaned['user_loyality_group'],prefix='user_loyality_group')], axis=1)
profile_df_cleaned['user_income_group'] = profile_df_cleaned['income'].apply(lambda x: income_group(x))
profile_df_cleaned = pd.concat([profile_df_cleaned.drop('user_income_group', axis=1),pd.get_dummies(profile_df_cleaned['user_income_group'],prefix='user_income_group')], axis=1)
profile_df_cleaned.drop(['id','age','became_member_on','gender','income'],axis=1,inplace=True)
return profile_df_cleaned
profile_df = clean_profile(profile)
profile_df
| user_gender_F | user_gender_M | user_gender_O | user_id | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 0 | 0 | 0610b486422d4921ae7d2bf64640c50b | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 3 | 1 | 0 | 0 | 78afa995795e4d85b5d9ceeca43f5fef | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 5 | 0 | 1 | 0 | e2127556f4f64592b11af22de27a7932 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 8 | 0 | 1 | 0 | 389bc3fa690240e798340f5a15918d5c | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 12 | 0 | 1 | 0 | 2eeac8d8feae4a8cad5a6af0499a211d | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 13 | 1 | 0 | 0 | aa4862eba776480b8bb9c68455b8c2e1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 14 | 0 | 1 | 0 | e12aeaf2d47d42479ea1c4ac3d8286c6 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 15 | 1 | 0 | 0 | 31dda685af34476cad5bc968bdb01c53 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 16 | 0 | 1 | 0 | 62cf5e10845442329191fc246e7bcea3 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 18 | 0 | 1 | 0 | 6445de3b47274c759400cd68131d91b4 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 19 | 1 | 0 | 0 | a448667f336b42c9a66fc5ffd5d73772 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 20 | 1 | 0 | 0 | 440cf1fd7580490c971d8c651ed962af | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 21 | 0 | 1 | 0 | 4b0da7e80e5945209a1fdddfe813dbe0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 22 | 1 | 0 | 0 | c27e0d6ab72c455a8bb66d980963de60 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 24 | 0 | 1 | 0 | f806632c011441378d4646567f357a21 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
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| 16988 | 0 | 1 | 0 | f653cf2d8bba42d0a53c2937ee2e5893 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 16990 | 1 | 0 | 0 | 79edb810789c447e8d212a324b44cc16 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 16992 | 1 | 0 | 0 | 400d0536e8794cbb855b0d882d67cbda | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 16993 | 0 | 1 | 0 | cb23b66c56f64b109d673d5e56574529 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 16995 | 1 | 0 | 0 | 6d5f3a774f3d4714ab0c092238f3a1d7 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 16996 | 0 | 1 | 0 | 2cb4f97358b841b9a9773a7aa05a9d77 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 16997 | 0 | 1 | 0 | 01d26f638c274aa0b965d24cefe3183f | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| 16998 | 1 | 0 | 0 | 9dc1421481194dcd9400aec7c9ae6366 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 16999 | 1 | 0 | 0 | e4052622e5ba45a8b96b59aba68cf068 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
14825 rows × 24 columns
profile['income'].describe()
count 14825.000000 mean 65404.991568 std 21598.299410 min 30000.000000 25% 49000.000000 50% 64000.000000 75% 80000.000000 max 120000.000000 Name: income, dtype: float64
profile['income'].hist()
<matplotlib.axes._subplots.AxesSubplot at 0x7fc91b9de400>
profile['age'].describe()
count 17000.000000 mean 62.531412 std 26.738580 min 18.000000 25% 45.000000 50% 58.000000 75% 73.000000 max 118.000000 Name: age, dtype: float64
profile['age'].hist()
<matplotlib.axes._subplots.AxesSubplot at 0x7fc91ba2d7b8>
transcript_df['transaction_amount'].describe()
count 290973 unique 5100 top freq 152653 Name: transaction_amount, dtype: object
transcript_protfolio_merged = pd.merge(transcript_df , portfolio_df, on='offer_id', how='outer')
transcript_protfolio_merged
| user_id | offer_id | transaction_amount | offer_days | offer_status_received | offer_status_viewed | offer_status_completed | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 78afa995795e4d85b5d9ceeca43f5fef | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 1 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 2 | da6c95e567f94dfdb54c16073807fcfe | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 3 | d0be9ff460964c3398a33ad9b2829f3a | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 4 | 01f46a5191424005af436cdf48a5da7c | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 5 | dbb37c0caad54f4a979a8121de79d0a2 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 6 | 3347e14dfe1f4526b14f3f849b2fc669 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 7 | 533435d3beb342c69c8d6a00947b7a4a | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 8 | 3f8b8ce1768d427588f442776e989b1e | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 9 | 481bcb3261a548bdb59df61d5e2a9ce3 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 10 | d0de5df4a59845fc865659b10adfb80e | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 11 | 383a3a796f3242a7bcded87c3f4af1b7 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 12 | 0e5b96f4d09a4bad94da8b04b0ed9a4e | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 13 | 09b7c854b70f495d883b9004d83d0137 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 14 | 9244de96cbbd4aca92a3c71979e72b47 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 15 | 26a2ab820a234213818a1a15e15eafee | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 16 | dfb467ce80d54545ae7ffc103b8fba35 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 17 | d5cc312f1ef64b43aa37d07bfcec99d4 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 18 | c1bb5a4b6d4a47ee8c5c009bbae056e3 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 19 | c02c98b9c5e94a5ca3c63c415ea0ad35 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 20 | 7df6c8ca03074f69aed1e52ed9b89fe4 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 21 | 3977011340cf47d08a23c4b3d6f6aef6 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 22 | b6d94c567b25454a9262c4f5c3ac996c | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 23 | b6d94c567b25454a9262c4f5c3ac996c | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 24 | fd45aee3900f4b3c88a35b53d0bf630b | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 25 | 667e1e1a4c8849d5879bc1d830e5a6b3 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 26 | 6cee7e5f6769472eb4151cc89eb039ce | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 27 | ff5a3d93c39e40d0a56a65673350cfab | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 28 | a9b0ed59ea614d80a17a5d436d887779 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 29 | a9b0ed59ea614d80a17a5d436d887779 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 290943 | f57fcd93d3e74e9b9bb9bc81a40a6612 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290944 | 3f935f28934b4151b6b7aadcb10c7a2b | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290945 | 3eb6aded21df4dcda69ba084c3dab2eb | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290946 | 7094d2b126a443369ad99924696810bd | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290947 | 7f0d9541dc284bb5b390c863644f04cd | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290948 | 14dc22654684405b9c4ece23bf234330 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290949 | ec5800ee8ae040708487b6473b1fbefc | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290950 | 2f86dc0c78c543ce9f01561fd5798bd4 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290951 | 1c9b9ecc88ba4983b6ecec2fa2636d49 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290952 | fef4f14201c44ddd915f504b7d88bf08 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290953 | b8397fc0004f4d70bb0374139d1c6ea3 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290954 | 4a5960fb3b054de39299788f537162d9 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290955 | df72761941ab427b9c8878508ad5814e | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290956 | ec70faa2792f4ee19d67dca4957d285f | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290957 | 8d501b5bda454c188e837579f8a1c50d | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290958 | 73c27012b82d4d6da8bee4b0eea67aef | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290959 | f428ef84305247ce98d2f7a59a70cc90 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290960 | 50b72821aa1a459698ad47ff4058c1ed | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290961 | 279318c88a9e451084f9c59a827f21a7 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290962 | 3964c9d017984279866a8496b9cd2156 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290963 | 8b5e47fbff5841518a90dee08cf42313 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290964 | 023a42cf62f742b795a975d56955e220 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290965 | 458339942fd54a30ab1c685d6d854358 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290966 | 2c2a1a03e7bf49febd39594ce9eb08bb | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290967 | d1a824d43588413981d90146cc781a13 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290968 | a3fa9c5ae07348f0ad9c6942a17e063b | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290969 | eb1ebe497d654c17b2fa99e40eb3d2d0 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290970 | 7f0d9541dc284bb5b390c863644f04cd | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290971 | 0c027f5f34dd4b9eba0a25785c611273 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290972 | a6f84f4e976f44508c358cc9aba6d2b3 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 30 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
290973 rows × 27 columns
transcript_protfolio_profile_merged = pd.merge(transcript_protfolio_merged, profile_df, on='user_id', how='outer')
transcript_protfolio_profile_merged
| user_id | offer_id | transaction_amount | offer_days | offer_status_received | offer_status_viewed | offer_status_completed | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 78afa995795e4d85b5d9ceeca43f5fef | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 1 | 78afa995795e4d85b5d9ceeca43f5fef | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 6 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 2 | 78afa995795e4d85b5d9ceeca43f5fef | 19.89 | 6 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 3 | 78afa995795e4d85b5d9ceeca43f5fef | 17.78 | 6 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 4 | 78afa995795e4d85b5d9ceeca43f5fef | 19.67 | 9 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 5 | 78afa995795e4d85b5d9ceeca43f5fef | 29.72 | 10 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 6 | 78afa995795e4d85b5d9ceeca43f5fef | 23.93 | 16 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 7 | 78afa995795e4d85b5d9ceeca43f5fef | 21.72 | 21 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 8 | 78afa995795e4d85b5d9ceeca43f5fef | 26.56 | 22 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 9 | 78afa995795e4d85b5d9ceeca43f5fef | 5a8bc65990b245e5a138643cd4eb9837 | 7 | 1 | 0 | 0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 10 | 78afa995795e4d85b5d9ceeca43f5fef | 5a8bc65990b245e5a138643cd4eb9837 | 9 | 0 | 1 | 0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 11 | 78afa995795e4d85b5d9ceeca43f5fef | f19421c1d4aa40978ebb69ca19b0e20d | 21 | 1 | 0 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 12 | 78afa995795e4d85b5d9ceeca43f5fef | f19421c1d4aa40978ebb69ca19b0e20d | 21 | 0 | 0 | 1 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 13 | 78afa995795e4d85b5d9ceeca43f5fef | f19421c1d4aa40978ebb69ca19b0e20d | 24 | 0 | 1 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 14 | 78afa995795e4d85b5d9ceeca43f5fef | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 15 | 78afa995795e4d85b5d9ceeca43f5fef | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 16 | 78afa995795e4d85b5d9ceeca43f5fef | ae264e3637204a6fb9bb56bc8210ddfd | 21 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 17 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 18 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 2 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 19 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 7 | 1 | 0 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 20 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 8 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 21 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 11 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 22 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 25.39 | 2 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 23 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 14.38 | 3 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 24 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 28.08 | 11 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 25 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 17.73 | 11 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 26 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 15.18 | 18 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 27 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 18.05 | 23 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 28 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 15.9 | 24 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 29 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 19.68 | 25 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 290943 | bc0c484263b94b0896f20c5e4fdf3585 | 3f207df678b143eea3cee63160fa8bed | 15 | 0 | 1 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290944 | d727102ac242449ab15f1bd1af28e6ff | 3f207df678b143eea3cee63160fa8bed | 14 | 1 | 0 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290945 | d727102ac242449ab15f1bd1af28e6ff | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290946 | d727102ac242449ab15f1bd1af28e6ff | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290947 | b52302342d674c9784218a66bf550cca | 3f207df678b143eea3cee63160fa8bed | 17 | 1 | 0 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290948 | b52302342d674c9784218a66bf550cca | ae264e3637204a6fb9bb56bc8210ddfd | 7 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290949 | b52302342d674c9784218a66bf550cca | ae264e3637204a6fb9bb56bc8210ddfd | 8 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290950 | b52302342d674c9784218a66bf550cca | ae264e3637204a6fb9bb56bc8210ddfd | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290951 | c00d1f6e8cba4787a00766232ae4711c | 3f207df678b143eea3cee63160fa8bed | 21 | 1 | 0 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290952 | c00d1f6e8cba4787a00766232ae4711c | 3f207df678b143eea3cee63160fa8bed | 24 | 0 | 1 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290953 | c00d1f6e8cba4787a00766232ae4711c | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290954 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 0 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290955 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 14 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290956 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 15 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290957 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290958 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290959 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 5 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290960 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290961 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290962 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 20 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290963 | 27228232d0a649a1abb48246eb5616f9 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 7 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290964 | 27228232d0a649a1abb48246eb5616f9 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 7 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290965 | 1bfe13d2453c4185a6486c6817e0d568 | ae264e3637204a6fb9bb56bc8210ddfd | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290966 | 1bfe13d2453c4185a6486c6817e0d568 | ae264e3637204a6fb9bb56bc8210ddfd | 16 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290967 | 307f96a6ea9d40daa5978bf244dcd735 | ae264e3637204a6fb9bb56bc8210ddfd | 21 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290968 | 307f96a6ea9d40daa5978bf244dcd735 | ae264e3637204a6fb9bb56bc8210ddfd | 22 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290969 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 14 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290970 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 16 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290971 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 17 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290972 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 17 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
290973 rows × 50 columns
df = transcript_protfolio_profile_merged.copy()
df_calculated = df.copy()
df_calculated
| user_id | offer_id | transaction_amount | offer_days | offer_status_received | offer_status_viewed | offer_status_completed | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 78afa995795e4d85b5d9ceeca43f5fef | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 1 | 78afa995795e4d85b5d9ceeca43f5fef | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 6 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 2 | 78afa995795e4d85b5d9ceeca43f5fef | 19.89 | 6 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 3 | 78afa995795e4d85b5d9ceeca43f5fef | 17.78 | 6 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 4 | 78afa995795e4d85b5d9ceeca43f5fef | 19.67 | 9 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 5 | 78afa995795e4d85b5d9ceeca43f5fef | 29.72 | 10 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 6 | 78afa995795e4d85b5d9ceeca43f5fef | 23.93 | 16 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 7 | 78afa995795e4d85b5d9ceeca43f5fef | 21.72 | 21 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 8 | 78afa995795e4d85b5d9ceeca43f5fef | 26.56 | 22 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 9 | 78afa995795e4d85b5d9ceeca43f5fef | 5a8bc65990b245e5a138643cd4eb9837 | 7 | 1 | 0 | 0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 10 | 78afa995795e4d85b5d9ceeca43f5fef | 5a8bc65990b245e5a138643cd4eb9837 | 9 | 0 | 1 | 0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 11 | 78afa995795e4d85b5d9ceeca43f5fef | f19421c1d4aa40978ebb69ca19b0e20d | 21 | 1 | 0 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 12 | 78afa995795e4d85b5d9ceeca43f5fef | f19421c1d4aa40978ebb69ca19b0e20d | 21 | 0 | 0 | 1 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 13 | 78afa995795e4d85b5d9ceeca43f5fef | f19421c1d4aa40978ebb69ca19b0e20d | 24 | 0 | 1 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 14 | 78afa995795e4d85b5d9ceeca43f5fef | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 15 | 78afa995795e4d85b5d9ceeca43f5fef | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 16 | 78afa995795e4d85b5d9ceeca43f5fef | ae264e3637204a6fb9bb56bc8210ddfd | 21 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 17 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 0 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 18 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 2 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 19 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 7 | 1 | 0 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 20 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 8 | 0 | 1 | 0 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 21 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 | 11 | 0 | 0 | 1 | 7.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 22 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 25.39 | 2 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 23 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 14.38 | 3 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 24 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 28.08 | 11 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 25 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 17.73 | 11 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 26 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 15.18 | 18 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 27 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 18.05 | 23 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 28 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 15.9 | 24 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 29 | d1a6fe4c241e4dbf8a4da6fd6c714ac5 | 19.68 | 25 | 0 | 0 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 290943 | bc0c484263b94b0896f20c5e4fdf3585 | 3f207df678b143eea3cee63160fa8bed | 15 | 0 | 1 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290944 | d727102ac242449ab15f1bd1af28e6ff | 3f207df678b143eea3cee63160fa8bed | 14 | 1 | 0 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290945 | d727102ac242449ab15f1bd1af28e6ff | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290946 | d727102ac242449ab15f1bd1af28e6ff | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290947 | b52302342d674c9784218a66bf550cca | 3f207df678b143eea3cee63160fa8bed | 17 | 1 | 0 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290948 | b52302342d674c9784218a66bf550cca | ae264e3637204a6fb9bb56bc8210ddfd | 7 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290949 | b52302342d674c9784218a66bf550cca | ae264e3637204a6fb9bb56bc8210ddfd | 8 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290950 | b52302342d674c9784218a66bf550cca | ae264e3637204a6fb9bb56bc8210ddfd | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | |
| 290951 | c00d1f6e8cba4787a00766232ae4711c | 3f207df678b143eea3cee63160fa8bed | 21 | 1 | 0 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290952 | c00d1f6e8cba4787a00766232ae4711c | 3f207df678b143eea3cee63160fa8bed | 24 | 0 | 1 | 0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290953 | c00d1f6e8cba4787a00766232ae4711c | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290954 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 0 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290955 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 14 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290956 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 15 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290957 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290958 | c00d1f6e8cba4787a00766232ae4711c | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 24 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
| 290959 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 5 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290960 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290961 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290962 | 27228232d0a649a1abb48246eb5616f9 | ae264e3637204a6fb9bb56bc8210ddfd | 20 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290963 | 27228232d0a649a1abb48246eb5616f9 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 7 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290964 | 27228232d0a649a1abb48246eb5616f9 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 7 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 290965 | 1bfe13d2453c4185a6486c6817e0d568 | ae264e3637204a6fb9bb56bc8210ddfd | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290966 | 1bfe13d2453c4185a6486c6817e0d568 | ae264e3637204a6fb9bb56bc8210ddfd | 16 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290967 | 307f96a6ea9d40daa5978bf244dcd735 | ae264e3637204a6fb9bb56bc8210ddfd | 21 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290968 | 307f96a6ea9d40daa5978bf244dcd735 | ae264e3637204a6fb9bb56bc8210ddfd | 22 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290969 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 14 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290970 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 16 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290971 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 17 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | |
| 290972 | 307f96a6ea9d40daa5978bf244dcd735 | 2298d6c36e964ae4a3e7e9706d1fb8c2 | 17 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
290973 rows × 50 columns
def offer_success_calculation(df_calculated):
df_calculated['offer_success'] = 0
df_calculated['offer_amount'] = 0
users = df_calculated['user_id'].unique()
for user in users:
df = df_calculated[df_calculated['user_id']==user]
offers_list = df['offer_id'].unique()
offers = []
for i in offers_list:
if (i != ''):
if pd.notnull(i):
offers.append(i)
for offer in offers:
end = df[(df['offer_id']==offer)]['offer_days'].max()
offer_idx = df[(df['offer_id']==offer)]
received_day_index = pd.to_numeric(df[(df['offer_id']==offer)]['offer_status_received']).nlargest(1).index[0]
received_day_value = pd.to_numeric(df[(df['offer_id']==offer)]['offer_status_received']).nlargest(1).iloc[0]
viewed_day_index = pd.to_numeric(df[(df['offer_id']==offer)]['offer_status_viewed']).nlargest(1).index[0]
viewed_day_value = pd.to_numeric(df[(df['offer_id']==offer)]['offer_status_viewed']).nlargest(1).iloc[0]
completed_day_index = pd.to_numeric(df[(df['offer_id']==offer)]['offer_status_completed']).nlargest(1).index[0]
completed_day_value = pd.to_numeric(df[(df['offer_id']==offer)]['offer_status_completed']).nlargest(1).iloc[0]
start = df[(df['offer_id']==offer) & (df['offer_status_received']==1)]['offer_days'].max()
duration = df[(df['offer_id']==offer)]['offer_duration'].iloc[0]
diff = end - start
received_day = offer_idx['offer_days'].loc[received_day_index]
viewed_day = offer_idx['offer_days'].loc[viewed_day_index]
completed_day = offer_idx['offer_days'].loc[completed_day_index]
offer_amount = pd.to_numeric(df[(df['offer_days']==completed_day)]['transaction_amount']).max()
summ = received_day_value + viewed_day_value + completed_day_value
success=False
if (diff <= duration) and (summ == 3) and (received_day <= viewed_day) and (viewed_day <= completed_day):
success=True
if (success==True):
df_calculated.loc[offer_idx.index,'offer_success'] = 1
if(offer_idx['offer_type_informational'].iloc[0] == 1):
df_calculated.loc[offer_idx.index,'offer_amount'] = 0
if(offer_idx['offer_type_discount'].iloc[0] == 1):
df_calculated.loc[offer_idx.index,'offer_amount'] = offer_amount
if(offer_idx['offer_type_bogo'].iloc[0] == 1):
df_calculated.loc[offer_idx.index,'offer_amount'] = offer_amount
return df_calculated
df_calculated = offer_success_calculation(df_calculated)
df_calculated.to_csv('df_calculated.csv',index=False)
df_final = pd.read_csv('df_calculated.csv')
data = df_final.copy()
data = df_final.copy()
data.drop(['user_id','offer_id','transaction_amount'],axis=1,inplace=True)
data.dropna(inplace=True)
data.to_csv('data.csv',index=False)
data = pd.read_csv('data.csv')
success_data = data[data['offer_success']==1]
success_data
| offer_days | offer_status_received | offer_status_viewed | offer_status_completed | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | offer_success | offer_amount | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7 | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 21.72 |
| 8 | 17 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 21.72 |
| 9 | 21 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 21.72 |
| 19 | 24 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 15.90 |
| 20 | 24 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 15.90 |
| 21 | 24 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 15.90 |
| 28 | 24 | 1 | 0 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 11.17 |
| 29 | 25 | 0 | 1 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 11.17 |
| 30 | 26 | 0 | 0 | 1 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 11.17 |
| 31 | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.74 |
| 32 | 18 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.74 |
| 33 | 20 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.74 |
| 36 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 37 | 22 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 38 | 23 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 39 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 37.10 |
| 40 | 25 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 37.10 |
| 41 | 28 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 37.10 |
| 44 | 7 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 33.49 |
| 45 | 7 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 33.49 |
| 46 | 11 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 33.49 |
| 49 | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 22.31 |
| 50 | 14 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 22.31 |
| 51 | 16 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 22.31 |
| 55 | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 14.70 |
| 56 | 15 | 0 | 1 | 0 | 7.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 14.70 |
| 57 | 16 | 0 | 0 | 1 | 7.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 14.70 |
| 85 | 14 | 1 | 0 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.62 |
| 86 | 14 | 0 | 1 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.62 |
| 87 | 14 | 0 | 0 | 1 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.62 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 134756 | 24 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 23.07 |
| 134757 | 25 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 23.07 |
| 134758 | 28 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 23.07 |
| 134776 | 14 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 134777 | 15 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 134778 | 24 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 134779 | 24 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 134780 | 28 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 134782 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 18.92 |
| 134783 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 18.92 |
| 134784 | 28 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 18.92 |
| 134792 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.26 |
| 134793 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.26 |
| 134794 | 28 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.26 |
| 134797 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 16.18 |
| 134798 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 16.18 |
| 134799 | 29 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 16.18 |
| 134813 | 14 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 134814 | 15 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 134815 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 134816 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 134817 | 29 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 134826 | 24 | 1 | 0 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 25.50 |
| 134827 | 25 | 0 | 1 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 25.50 |
| 134828 | 29 | 0 | 0 | 1 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 25.50 |
| 134845 | 14 | 1 | 0 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 134846 | 14 | 0 | 1 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 134847 | 24 | 1 | 0 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 134848 | 25 | 0 | 1 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 134849 | 29 | 0 | 0 | 1 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
57834 rows × 49 columns
success_data.to_csv('success_data.csv')
offer_columns = ['offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7','offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2','offer_id__2906b810c7d4411798c6938adc9daaa5','offer_id__3f207df678b143eea3cee63160fa8bed','offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0','offer_id__5a8bc65990b245e5a138643cd4eb9837','offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9','offer_id__ae264e3637204a6fb9bb56bc8210ddfd','offer_id__f19421c1d4aa40978ebb69ca19b0e20d','offer_id__fafdcd668e3743c1bb461111dcafc2a4']
offer_columns
['offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7', 'offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2', 'offer_id__2906b810c7d4411798c6938adc9daaa5', 'offer_id__3f207df678b143eea3cee63160fa8bed', 'offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0', 'offer_id__5a8bc65990b245e5a138643cd4eb9837', 'offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9', 'offer_id__ae264e3637204a6fb9bb56bc8210ddfd', 'offer_id__f19421c1d4aa40978ebb69ca19b0e20d', 'offer_id__fafdcd668e3743c1bb461111dcafc2a4']
success_data=pd.read_csv('success_data.csv').drop('Unnamed: 0',axis=1)
success_data
| offer_days | offer_status_received | offer_status_viewed | offer_status_completed | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | offer_success | offer_amount | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 21.72 |
| 1 | 17 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 21.72 |
| 2 | 21 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 21.72 |
| 3 | 24 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 15.90 |
| 4 | 24 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 15.90 |
| 5 | 24 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 15.90 |
| 6 | 24 | 1 | 0 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 11.17 |
| 7 | 25 | 0 | 1 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 11.17 |
| 8 | 26 | 0 | 0 | 1 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 11.17 |
| 9 | 17 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.74 |
| 10 | 18 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.74 |
| 11 | 20 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.74 |
| 12 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 13 | 22 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 14 | 23 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 15 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 37.10 |
| 16 | 25 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 37.10 |
| 17 | 28 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 37.10 |
| 18 | 7 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 33.49 |
| 19 | 7 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 33.49 |
| 20 | 11 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 33.49 |
| 21 | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 22.31 |
| 22 | 14 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 22.31 |
| 23 | 16 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 22.31 |
| 24 | 14 | 1 | 0 | 0 | 7.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 14.70 |
| 25 | 15 | 0 | 1 | 0 | 7.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 14.70 |
| 26 | 16 | 0 | 0 | 1 | 7.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 14.70 |
| 27 | 14 | 1 | 0 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.62 |
| 28 | 14 | 0 | 1 | 0 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.62 |
| 29 | 14 | 0 | 0 | 1 | 5.0 | 5.0 | 5.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.62 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 57804 | 24 | 1 | 0 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 23.07 |
| 57805 | 25 | 0 | 1 | 0 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 23.07 |
| 57806 | 28 | 0 | 0 | 1 | 7.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 23.07 |
| 57807 | 14 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 57808 | 15 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 57809 | 24 | 1 | 0 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 57810 | 24 | 0 | 1 | 0 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 57811 | 28 | 0 | 0 | 1 | 7.0 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 31.18 |
| 57812 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 18.92 |
| 57813 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 18.92 |
| 57814 | 28 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 18.92 |
| 57815 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.26 |
| 57816 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.26 |
| 57817 | 28 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.26 |
| 57818 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 16.18 |
| 57819 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 16.18 |
| 57820 | 29 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 16.18 |
| 57821 | 14 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 57822 | 15 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 57823 | 24 | 1 | 0 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 57824 | 24 | 0 | 1 | 0 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 57825 | 29 | 0 | 0 | 1 | 10.0 | 10.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 27.11 |
| 57826 | 24 | 1 | 0 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 25.50 |
| 57827 | 25 | 0 | 1 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 25.50 |
| 57828 | 29 | 0 | 0 | 1 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 25.50 |
| 57829 | 14 | 1 | 0 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 57830 | 14 | 0 | 1 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 57831 | 24 | 1 | 0 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 57832 | 25 | 0 | 1 | 0 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
| 57833 | 29 | 0 | 0 | 1 | 5.0 | 10.0 | 10.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 26.79 |
57834 rows × 49 columns
success_data[(success_data['offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7']==1)]
| offer_days | offer_status_received | offer_status_viewed | offer_status_completed | offer_duration | offer_difficulty | offer_reward | offer_type_bogo | offer_type_discount | offer_type_informational | offer_channel_web | offer_channel_email | offer_channel_mobile | offer_channel_social | offer_id__0b1e1539f2cc45b7b9fa7c272da2e1d7 | offer_id__2298d6c36e964ae4a3e7e9706d1fb8c2 | offer_id__2906b810c7d4411798c6938adc9daaa5 | offer_id__3f207df678b143eea3cee63160fa8bed | offer_id__4d5c57ea9a6940dd891ad53e9dbe8da0 | offer_id__5a8bc65990b245e5a138643cd4eb9837 | offer_id__9b98b8c7a33c4b65b9aebfe6a799e6d9 | offer_id__ae264e3637204a6fb9bb56bc8210ddfd | offer_id__f19421c1d4aa40978ebb69ca19b0e20d | offer_id__fafdcd668e3743c1bb461111dcafc2a4 | user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | offer_success | offer_amount | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 12 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 13 | 22 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 14 | 23 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 713.12 |
| 48 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 20.05 |
| 49 | 23 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 20.05 |
| 50 | 24 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 20.05 |
| 57 | 7 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 27.74 |
| 58 | 9 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 27.74 |
| 59 | 12 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 27.74 |
| 72 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.09 |
| 73 | 23 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.09 |
| 74 | 26 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.09 |
| 99 | 17 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 20.28 |
| 100 | 18 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 20.28 |
| 101 | 21 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 20.28 |
| 146 | 7 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 34.04 |
| 147 | 7 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 34.04 |
| 148 | 12 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 34.04 |
| 149 | 14 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 34.04 |
| 150 | 21 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 34.04 |
| 154 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 30.03 |
| 155 | 22 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 30.03 |
| 156 | 24 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1 | 30.03 |
| 163 | 14 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 9.63 |
| 164 | 17 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 9.63 |
| 165 | 18 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 9.63 |
| 169 | 14 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 15.51 |
| 170 | 14 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 15.51 |
| 171 | 17 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 15.51 |
| 184 | 21 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 29.07 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 34667 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 6.97 |
| 34668 | 26 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 6.97 |
| 34669 | 29 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 6.97 |
| 34688 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 23.64 |
| 34689 | 26 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 23.64 |
| 34690 | 26 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 23.64 |
| 34706 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 30.20 |
| 34707 | 25 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 30.20 |
| 34708 | 25 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1 | 30.20 |
| 34718 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.48 |
| 34719 | 28 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.48 |
| 34720 | 28 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.48 |
| 34724 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 22.49 |
| 34725 | 24 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 22.49 |
| 34726 | 25 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 22.49 |
| 34748 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.31 |
| 34749 | 24 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.31 |
| 34750 | 28 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1 | 22.31 |
| 34784 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.47 |
| 34785 | 24 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.47 |
| 34786 | 29 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 21.47 |
| 34795 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.76 |
| 34796 | 24 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.76 |
| 34797 | 25 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 10.76 |
| 34846 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 24.04 |
| 34847 | 25 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 24.04 |
| 34848 | 27 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1 | 24.04 |
| 34865 | 24 | 1 | 0 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 18.04 |
| 34866 | 27 | 0 | 1 | 0 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 18.04 |
| 34867 | 29 | 0 | 0 | 1 | 10.0 | 20.0 | 5.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 | 18.04 |
3325 rows × 49 columns
successful_offers = []
for i in offer_columns:
successful_offers.append(success_data[success_data[i]==1])
offer_features = ['offer_success','offer_amount','offer_days','offer_status_received','offer_status_viewed','offer_status_completed','offer_duration','offer_difficulty','offer_reward','offer_type_bogo','offer_type_discount','offer_type_informational','offer_channel_web','offer_channel_email','offer_channel_mobile','offer_channel_social']
successful_offers_demographic = []
for df in successful_offers:
successful_offers_demographic.append(df.drop(offer_columns+offer_features,axis=1))
successful_offers_demographic[0]
| user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 12 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 13 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 14 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 48 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 49 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 50 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 57 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 58 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 59 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 72 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 73 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 74 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 99 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 100 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 101 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 146 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 147 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 148 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 149 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 150 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 154 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 155 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 156 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 163 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 164 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 165 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 169 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 170 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 171 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 184 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 34667 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34668 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34669 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34688 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34689 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34690 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34706 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
| 34707 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
| 34708 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
| 34718 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34719 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34720 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34724 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34725 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34726 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34748 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34749 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34750 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 34784 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34785 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34786 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34795 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34796 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34797 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34846 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34847 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34848 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 34865 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34866 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 34867 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3325 rows × 23 columns
successful_offers_demographic_sums = []
for i in range(0,10):
successful_offers_demographic_sums.append(successful_offers_demographic[i].sum(axis = 0))
successful_offers_demographic_sums[i] = successful_offers_demographic_sums[i].append(pd.Series({'success_count' :successful_offers_demographic[i].shape[0]}))
successful_offers_demographic_sums[i] = successful_offers_demographic_sums[i].append(pd.Series({'offer_id' :offer_columns[i].split('_')[3]}))
successful_offers_demographic_sums[0]
user_gender_F 1559 user_gender_M 1668 user_gender_O 98 user_age_group_1 45 user_age_group_2 69 user_age_group_3 129 user_age_group_4 511 user_age_group_5 774 user_age_group_6 844 user_age_group_7 953 user_loyality_group_2 46 user_loyality_group_3 167 user_loyality_group_4 393 user_loyality_group_5 1008 user_loyality_group_6 1173 user_loyality_group_7 538 user_income_group_1 79 user_income_group_2 198 user_income_group_3 1102 user_income_group_4 623 user_income_group_5 539 user_income_group_6 476 user_income_group_7 308 success_count 3325 offer_id 0b1e1539f2cc45b7b9fa7c272da2e1d7 dtype: object
successful_offers_demographic_sums[0]
user_gender_F 1559 user_gender_M 1668 user_gender_O 98 user_age_group_1 45 user_age_group_2 69 user_age_group_3 129 user_age_group_4 511 user_age_group_5 774 user_age_group_6 844 user_age_group_7 953 user_loyality_group_2 46 user_loyality_group_3 167 user_loyality_group_4 393 user_loyality_group_5 1008 user_loyality_group_6 1173 user_loyality_group_7 538 user_income_group_1 79 user_income_group_2 198 user_income_group_3 1102 user_income_group_4 623 user_income_group_5 539 user_income_group_6 476 user_income_group_7 308 success_count 3325 offer_id 0b1e1539f2cc45b7b9fa7c272da2e1d7 dtype: object
successful_offers_demographic_sums_df = pd.DataFrame(successful_offers_demographic_sums)
successful_offers_demographic_sums_df
| user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | success_count | offer_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1559.0 | 1668.0 | 98.0 | 45.0 | 69.0 | 129.0 | 511.0 | 774.0 | 844.0 | 953.0 | 46.0 | 167.0 | 393.0 | 1008.0 | 1173.0 | 538.0 | 79.0 | 198.0 | 1102.0 | 623.0 | 539.0 | 476.0 | 308.0 | 3325.0 | 0b1e1539f2cc45b7b9fa7c272da2e1d7 |
| 1 | 4561.0 | 5755.0 | 154.0 | 291.0 | 374.0 | 888.0 | 1505.0 | 2148.0 | 2322.0 | 2942.0 | 214.0 | 583.0 | 1254.0 | 2673.0 | 3858.0 | 1888.0 | 714.0 | 1208.0 | 3324.0 | 1918.0 | 1146.0 | 930.0 | 1230.0 | 10470.0 | 2298d6c36e964ae4a3e7e9706d1fb8c2 |
| 2 | 2333.0 | 2920.0 | 114.0 | 107.0 | 112.0 | 309.0 | 818.0 | 1166.0 | 1351.0 | 1504.0 | 130.0 | 294.0 | 724.0 | 1461.0 | 1860.0 | 898.0 | 256.0 | 391.0 | 1785.0 | 1024.0 | 759.0 | 635.0 | 517.0 | 5367.0 | 2906b810c7d4411798c6938adc9daaa5 |
| 3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3f207df678b143eea3cee63160fa8bed |
| 4 | 3806.0 | 3327.0 | 107.0 | 141.0 | 145.0 | 457.0 | 945.0 | 1694.0 | 1678.0 | 2180.0 | 93.0 | 219.0 | 961.0 | 1993.0 | 2984.0 | 990.0 | 261.0 | 552.0 | 1990.0 | 1476.0 | 953.0 | 828.0 | 1180.0 | 7240.0 | 4d5c57ea9a6940dd891ad53e9dbe8da0 |
| 5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5a8bc65990b245e5a138643cd4eb9837 |
| 6 | 2462.0 | 2859.0 | 116.0 | 94.0 | 107.0 | 348.0 | 858.0 | 1313.0 | 1242.0 | 1475.0 | 120.0 | 227.0 | 809.0 | 1378.0 | 1943.0 | 960.0 | 255.0 | 365.0 | 1815.0 | 1024.0 | 738.0 | 648.0 | 592.0 | 5437.0 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 |
| 7 | 3278.0 | 3312.0 | 119.0 | 150.0 | 152.0 | 473.0 | 985.0 | 1472.0 | 1655.0 | 1822.0 | 86.0 | 149.0 | 853.0 | 1878.0 | 2632.0 | 1111.0 | 316.0 | 579.0 | 2169.0 | 1205.0 | 902.0 | 722.0 | 816.0 | 6709.0 | ae264e3637204a6fb9bb56bc8210ddfd |
| 8 | 3935.0 | 4583.0 | 146.0 | 256.0 | 260.0 | 667.0 | 1071.0 | 1918.0 | 2044.0 | 2448.0 | 152.0 | 391.0 | 1052.0 | 2386.0 | 3276.0 | 1407.0 | 492.0 | 859.0 | 2785.0 | 1577.0 | 962.0 | 876.0 | 1113.0 | 8664.0 | f19421c1d4aa40978ebb69ca19b0e20d |
| 9 | 4764.0 | 5730.0 | 128.0 | 216.0 | 327.0 | 979.0 | 1404.0 | 2183.0 | 2617.0 | 2896.0 | 245.0 | 565.0 | 1510.0 | 2729.0 | 3666.0 | 1907.0 | 751.0 | 1138.0 | 3434.0 | 1857.0 | 1181.0 | 1036.0 | 1225.0 | 10622.0 | fafdcd668e3743c1bb461111dcafc2a4 |
df = successful_offers_demographic_sums_df
df
| user_gender_F | user_gender_M | user_gender_O | user_age_group_1 | user_age_group_2 | user_age_group_3 | user_age_group_4 | user_age_group_5 | user_age_group_6 | user_age_group_7 | user_loyality_group_2 | user_loyality_group_3 | user_loyality_group_4 | user_loyality_group_5 | user_loyality_group_6 | user_loyality_group_7 | user_income_group_1 | user_income_group_2 | user_income_group_3 | user_income_group_4 | user_income_group_5 | user_income_group_6 | user_income_group_7 | success_count | offer_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1559.0 | 1668.0 | 98.0 | 45.0 | 69.0 | 129.0 | 511.0 | 774.0 | 844.0 | 953.0 | 46.0 | 167.0 | 393.0 | 1008.0 | 1173.0 | 538.0 | 79.0 | 198.0 | 1102.0 | 623.0 | 539.0 | 476.0 | 308.0 | 3325.0 | 0b1e1539f2cc45b7b9fa7c272da2e1d7 |
| 1 | 4561.0 | 5755.0 | 154.0 | 291.0 | 374.0 | 888.0 | 1505.0 | 2148.0 | 2322.0 | 2942.0 | 214.0 | 583.0 | 1254.0 | 2673.0 | 3858.0 | 1888.0 | 714.0 | 1208.0 | 3324.0 | 1918.0 | 1146.0 | 930.0 | 1230.0 | 10470.0 | 2298d6c36e964ae4a3e7e9706d1fb8c2 |
| 2 | 2333.0 | 2920.0 | 114.0 | 107.0 | 112.0 | 309.0 | 818.0 | 1166.0 | 1351.0 | 1504.0 | 130.0 | 294.0 | 724.0 | 1461.0 | 1860.0 | 898.0 | 256.0 | 391.0 | 1785.0 | 1024.0 | 759.0 | 635.0 | 517.0 | 5367.0 | 2906b810c7d4411798c6938adc9daaa5 |
| 3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3f207df678b143eea3cee63160fa8bed |
| 4 | 3806.0 | 3327.0 | 107.0 | 141.0 | 145.0 | 457.0 | 945.0 | 1694.0 | 1678.0 | 2180.0 | 93.0 | 219.0 | 961.0 | 1993.0 | 2984.0 | 990.0 | 261.0 | 552.0 | 1990.0 | 1476.0 | 953.0 | 828.0 | 1180.0 | 7240.0 | 4d5c57ea9a6940dd891ad53e9dbe8da0 |
| 5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5a8bc65990b245e5a138643cd4eb9837 |
| 6 | 2462.0 | 2859.0 | 116.0 | 94.0 | 107.0 | 348.0 | 858.0 | 1313.0 | 1242.0 | 1475.0 | 120.0 | 227.0 | 809.0 | 1378.0 | 1943.0 | 960.0 | 255.0 | 365.0 | 1815.0 | 1024.0 | 738.0 | 648.0 | 592.0 | 5437.0 | 9b98b8c7a33c4b65b9aebfe6a799e6d9 |
| 7 | 3278.0 | 3312.0 | 119.0 | 150.0 | 152.0 | 473.0 | 985.0 | 1472.0 | 1655.0 | 1822.0 | 86.0 | 149.0 | 853.0 | 1878.0 | 2632.0 | 1111.0 | 316.0 | 579.0 | 2169.0 | 1205.0 | 902.0 | 722.0 | 816.0 | 6709.0 | ae264e3637204a6fb9bb56bc8210ddfd |
| 8 | 3935.0 | 4583.0 | 146.0 | 256.0 | 260.0 | 667.0 | 1071.0 | 1918.0 | 2044.0 | 2448.0 | 152.0 | 391.0 | 1052.0 | 2386.0 | 3276.0 | 1407.0 | 492.0 | 859.0 | 2785.0 | 1577.0 | 962.0 | 876.0 | 1113.0 | 8664.0 | f19421c1d4aa40978ebb69ca19b0e20d |
| 9 | 4764.0 | 5730.0 | 128.0 | 216.0 | 327.0 | 979.0 | 1404.0 | 2183.0 | 2617.0 | 2896.0 | 245.0 | 565.0 | 1510.0 | 2729.0 | 3666.0 | 1907.0 | 751.0 | 1138.0 | 3434.0 | 1857.0 | 1181.0 | 1036.0 | 1225.0 | 10622.0 | fafdcd668e3743c1bb461111dcafc2a4 |
df = successful_offers_demographic_sums_df
gender_group = ['user_gender_F', 'user_gender_M', 'user_gender_O']
gender_group
['user_gender_F', 'user_gender_M', 'user_gender_O']
gender_group_info = ['Male','Female', 'Other']
gender_group_info
['Male', 'Female', 'Other']
age_group = ['user_age_group_1', 'user_age_group_2', 'user_age_group_3', 'user_age_group_4', 'user_age_group_5', 'user_age_group_6', 'user_age_group_7']
age_group
['user_age_group_1', 'user_age_group_2', 'user_age_group_3', 'user_age_group_4', 'user_age_group_5', 'user_age_group_6', 'user_age_group_7']
age_group_info = ['21 or younger','25 - 22', '35 - 26', '45 - 36', '55 - 46', '65 - 56', '66 or older']
age_group_info
['21 or younger', '25 - 22', '35 - 26', '45 - 36', '55 - 46', '65 - 56', '66 or older']
loyality_group = ['user_loyality_group_1', 'user_loyality_group_2', 'user_loyality_group_3', 'user_loyality_group_4', 'user_loyality_group_5', 'user_loyality_group_6', 'user_loyality_group_7']
loyality_group
['user_loyality_group_1', 'user_loyality_group_2', 'user_loyality_group_3', 'user_loyality_group_4', 'user_loyality_group_5', 'user_loyality_group_6', 'user_loyality_group_7']
loyality_group_info = ['2013 or newer','2014 - 2013', '2015 - 2014', '2016 - 2015', '2017 - 2016', '2018 - 2017', '2018 or newer']
loyality_group_info
['2013 or newer', '2014 - 2013', '2015 - 2014', '2016 - 2015', '2017 - 2016', '2018 - 2017', '2018 or newer']
income_group = ['user_income_group_1', 'user_income_group_2', 'user_income_group_3', 'user_income_group_4', 'user_income_group_5', 'user_income_group_6', 'user_income_group_7']
income_group
['user_income_group_1', 'user_income_group_2', 'user_income_group_3', 'user_income_group_4', 'user_income_group_5', 'user_income_group_6', 'user_income_group_7']
income_group_info = ['35k or less','45k - 36k', '65k - 46k', '75k - 66k', '85k - 76k', '95k - 86k', '96k or more']
income_group_info
['35k or less', '45k - 36k', '65k - 46k', '75k - 66k', '85k - 76k', '95k - 86k', '96k or more']
# Create figure with secondary y-axis
from plotly.subplots import make_subplots
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
for (feature, info) in zip(gender_group, gender_group_info):
fig.add_trace(
go.Scatter(x=list(df.offer_id), y=df[feature], name=info),
)
# Add figure title
fig.update_layout(
title_text="User Gender For Each Offer"
)
# Set x-axis title
fig.update_xaxes(title_text="Offer")
# Set y-axes titles
fig.update_yaxes(title_text="Count Of User Group Per Successful Offer")
fig.show()
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
for (feature, info) in zip(age_group, age_group_info):
fig.add_trace(
go.Scatter(x=list(df.offer_id), y=df[feature], name=info),
)
# Add figure title
fig.update_layout(
title_text="User Age Group For Each Offer"
)
# Set x-axis title
fig.update_xaxes(title_text="Offer")
# Set y-axes titles
fig.update_yaxes(title_text="Count Of User Group Per Successful Offer")
fig.show()
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
for (feature, info) in zip(income_group, income_group_info):
fig.add_trace(
go.Scatter(x=list(df.offer_id), y=df[feature], name=info),
)
# Add figure title
fig.update_layout(
title_text="User Income Group For Each Offer"
)
# Set x-axis title
fig.update_xaxes(title_text="Offer")
# Set y-axes titles
fig.update_yaxes(title_text="Number Of User Group Per Successful Offer")
fig.show()
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
loyality_group.pop(0) # no users in group 1
loyality_group_info.pop(0) # no users in group 1
# Add traces
for (feature, info) in zip(loyality_group, loyality_group_info):
fig.add_trace(
go.Scatter(x=list(df.offer_id), y=df[feature], name=info),
)
# Add figure title
fig.update_layout(
title_text="User Loyality Group For Each Offer"
)
# Set x-axis title
fig.update_xaxes(title_text="Offer")
# Set y-axes titles
fig.update_yaxes(title_text="Number Of User Group Per Successful Offer")
fig.show()
#Mostly user_gender_M, user_age_group_7, user_income_group_3, user_loyality_group_6
After studying all the data and the graphs generated after thorough investigation and transformations of the givine data, I can say the following:
All Offers are succesfful for this user demographic:
Mostly Female, 65 years of age or more, Earns between 45000 and 65000 and Joined recently in 2018 - 2017 period.